DocumentCode :
2951334
Title :
On-Line Production Cost Optimization in High Performance Machining Operations through AI Techniques
Author :
Silva, Jorge A. ; Siller, Héctor R. ; Kitazawa, G. ; Abellan-Nebot, J.V.
Author_Institution :
Centre for Innovation in Design & Technol., Tec de Monterrey (ITESM), Monterrey, Mexico
fYear :
2011
fDate :
15-18 Nov. 2011
Firstpage :
47
Lastpage :
52
Abstract :
This paper proposes an on-line adaptive control with optimization (ACO) system for optimizing the production cost subjected to quality constraints in high performance machining operations of hardened steel. Unlike traditional approaches for optimizing production cost, this paper deals with optimizing the cutting operation considering the real state of the cutting-tool. Artificial intelligence techniques for modeling (Artificial Neural Networks) and optimizing (Genetic Algorithms and Mesh Adaptive Direct Search algorithms) are applied for this purpose.
Keywords :
artificial intelligence; costing; cutting; cutting tools; genetic algorithms; machining; neural nets; production engineering computing; steel; ACO system; AI technique; artificial intelligence; artificial neural network; cutting operation; cutting-tool; genetic algorithm; hardened steel; high performance machining operation; mesh adaptive direct search algorithm; online adaptive control; online production cost optimization; quality constraint; Cutting tools; Estimation; Machining; Optimization; Rough surfaces; Surface roughness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2011 IEEE
Conference_Location :
Cuernavaca, Morelos
Print_ISBN :
978-1-4577-1879-3
Type :
conf
DOI :
10.1109/CERMA.2011.15
Filename :
6125808
Link To Document :
بازگشت